Fractional order controller based maximum power point tracking controller for wind turbine system

Karad, Shivaji; Thakur, Ritula

doi:10.1080/00207217.2021.1941296

Cited by 9 publications

(3 citation statements)

References 33 publications

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“…Hence, wind power generation systems need to adopt different control methods according to diverse wind speed intervals [17]. In order to extract the maximum energy from the WECS in the MPPT interval where the WECS produces the maximum available wind power, it is necessary to design a maximum power point tracking controller (MPPT) [18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Dahmane,

Boulaoutaq,

Bouachrine

et al. 2023

Journal of Robotics and Control

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In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm 𝑃𝑂 and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control. This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control.

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Section: Introductionmentioning

confidence: 99%

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Dahmane,

Boulaoutaq,

Bouachrine

et al. 2023

Journal of Robotics and Control

View full text Add to dashboard Cite

show abstract

“…If the step size is large, it causes power fluctuations; if it is small, the response time of the model to changes in wind speed increases. To address these challenges, hybrid [13][14] , modified [15][16][17][18] , and optimized [19][20] versions of traditional indirect and direct power control algorithms have been presented. These hybrid and modified methods solve challenges associated with conventional algorithms.…”

Section: Introduction1mentioning

confidence: 99%

A Novel Modified Fuzzy-Predictive Control of Permanent Magnet Synchronous Generator Based Wind Energy Conversion System

Akbari,

Shadlu

2023

Chin. J. Electr. Eng.

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A wind energy conversion system (WECS) based on a permanent magnet synchronous generator (PMSG) is an effective solution for renewable energy generation in modern power systems. The main advantages of PMSG include high performance at high and low speeds, minimal control effort owing to lower rotor inertia, self-excitation, high reliability, and simplicity of structure compared with induction generators. However, the intermittent nature of wind energy implies that maximum efficiency is not obtained from this system. Accordingly, maximum power point tracking (MPPT) in wind turbine systems has been proposed to address this problem. Traditional MPPT strategies suffer from severe output power fluctuations, low efficiency, and significant ripples in turbine rotation speed. This paper presents a novel MPPT control strategy based on fuzzy logic control (FLC) and model predictive control (MPC) to extract the maximum power from a PMSG-WECS and control the machine-side and grid-side converters. The simulation results obtained from Matlab/Simulink confirm the superiority of the control model in eliminating the output power fluctuations of the wind generators and accurately tracking the maximum power point. A comparative study between conventional MPPT and control methods is also conducted.

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“…Some resent and relevant results on FOC applied to PECs can be summarized as follows: highly sophisticated proposals that included either fuzzy- or MPPT-based PID controllers were suggested in [ 15 , 16 ] to deal with disturbances and uncertainties when regulating output voltage in a buck converter. In addition, controller parameters tuning was performed through optimization algorithms.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Its Implementation Impact of Two-Modes Controller Fractional Approximation for Buck Converters

2022

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Additional degrees of freedom in a fractional-order control strategy for power electronic converters are well received despite the lack of reliable tuning methods. Despite artificial/swarm intelligence techniques have been used to adjust controller parameters to improve more than one characteristic/property at the same time, smart tuning not always leads to realizable structures or reachable parameter values. Thus, adjustment boundaries to ensure controller viability are needed. In this manuscript the fractional-order approach is described in terms of El-Khazali biquadratic module, which produces the lowest order approximation, instead of using a definition. A two-modes controller structure is synthesize depending on uncontrolled plant needs and parameters are adjusted through particle swarm and genetic optimization algorithms for comparison. Two error-based minimization criteria are used to consider output performance into the process. Two restrictions complement the optimization scheme, one seeks to ensure desired robustness while the other prevents from synthesizing a high-gain controller. Optimization results showed similarity between minima obtained and significant difference between parameters of those controller optimized without the proposed constraints was determined. Numerical and experimental results are provide to validate proposed approach effectiveness. Effective regulation, good tracking characteristic and robustness in the presence of load variations are the main results.

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Fractional order controller based maximum power point tracking controller for wind turbine system

Cited by 9 publications

References 33 publications

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

A Novel Modified Fuzzy-Predictive Control of Permanent Magnet Synchronous Generator Based Wind Energy Conversion System

Optimization and Its Implementation Impact of Two-Modes Controller Fractional Approximation for Buck Converters

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